Databricks is a data analytics platform. It mostly works on an Apache Spark framework, an open-source cluster computing framework that provides programmers with an interface to develop applications in Python or Scala. It also offers some cutting-edge machine learning applications on top of it. It is based in San Francisco and was founded by the team behind the Apache Spark project.

Why Databricks?

• It comes with BI, SQL and Scala drag and drop visual programming that enables easy data discovery.
• Its graphical workflow view makes the whole development process much easier to understand.
• It’s strict quality control due to Databricks’ strong focus on code reusability and collaboration via the Databricks’ Notebook sharing system.
• It is scalable and can handle both structured and semi-structured data types.
• Databricks can be used with various languages like R or Python, allowing for large-scale data analysis.
• Its datasets can be a part of a single or distributed system and run on clusters to support high-speed processing and faster results.
• Databricks also has the ability to manage Spark programs for users, providing version control, collaboration tools, and allowing for easy scheduling of workflows among other useful features.